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dc.contributor.authorAshraf, M.A.
dc.contributor.authorAli, B.
dc.contributor.authorBrown, J.K.
dc.contributor.authorShahid, I.
dc.contributor.authorYu, N.
dc.date.accessioned2024-08-06T03:49:47Z
dc.date.available2024-08-06T03:49:47Z
dc.date.issued2023-02-09
dc.identifier.citationAshraf, M.A.; Ali, B.; Brown, J.K.; Shahid, I.; Yu, N. In Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava. Viruses 2023, 15, 486. https://doi.org/10.3390/v15020486
dc.identifier.issn1999-4915
dc.identifier.pmid36851701
dc.identifier.doi10.3390/v15020486
dc.identifier.urihttp://hdl.handle.net/10150/673837
dc.description.abstractCassava mosaic disease (CMD) is caused by several divergent species belonging to the genus Begomovirus (Geminiviridae) transmitted by the whitefly Bemisia tabaci cryptic species group. In India and other parts of Asia, the Indian cassava mosaic virus-Kerala (ICMV-Ker) is an emergent begomovirus of cassava causing damage that results in reduced yield loss and tuber quality. Double-stranded RNA-mediated interference (RNAi) is an evolutionary conserved mechanism in eukaryotes and highly effective, innate defense system to inhibit plant viral replication and/or translation. The objective of this study was to identify and characterize cassava genome-encoded microRNAs (mes-miRNA) that are predicted to target ICMV-Ker ssDNA-encoded mRNAs, based on four in silico algorithms: miRanda, RNA22, Tapirhybrid, and psRNA. The goal is to deploy the predicted miRNAs to trigger RNAi and develop cassava plants with resistance to ICMV-Ker. Experimentally validated mature cassava miRNA sequences (n = 175) were downloaded from the miRBase biological database and aligned with the ICMV-Ker genome. The miRNAs were evaluated for base-pairing with the cassava miRNA seed regions and to complementary binding sites within target viral mRNAs. Among the 175 locus-derived mes-miRNAs evaluated, one cassava miRNA homolog, mes-miR1446a, was identified to have a predicted miRNA target binding site, at position 2053 of the ICMV-Ker genome. To predict whether the cassava miRNA might bind predicted ICMV-Ker mRNA target(s) that could disrupt viral infection of cassava plants, a cassava locus-derived miRNA–mRNA regulatory network was constructed using Circos software. The in silico-predicted cassava locus-derived mes-miRNA-mRNA network corroborated interactions between cassava mature miRNAs and the ICMV-Ker genome that warrant in vivo analysis, which could lead to the development of ICMV-Ker resistant cassava plants. © 2023 by the authors.
dc.language.isoen
dc.publisherMDPI
dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectbegomovirus
dc.subjectcomputational miRNA algorithms
dc.subjectIndian cassava mosaic virus-Kerala
dc.subjectnon-coding RNA
dc.subjectR-language
dc.subjectRNA interference
dc.subjectvirus resistance
dc.titleIn Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava
dc.typeArticle
dc.typetext
dc.contributor.departmentSchool of Plant Sciences, The University of Arizona
dc.identifier.journalViruses
dc.description.noteOpen access journal
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
dc.eprint.versionFinal Published Version
dc.source.journaltitleViruses
refterms.dateFOA2024-08-06T03:49:47Z


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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license.
Except where otherwise noted, this item's license is described as © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license.